B

binomial distribution
7.3 Using the Central Limit Theorem,
9.3 Distribution Needed for Hypothesis Testing

binomial probability distribution
4.3 Binomial Distribution (Optional)

bivariate
Introduction

Blinding
1.4 Experimental Design and Ethics

Box plots
2.4 Box Plots

box-and-whisker plots
2.4 Box Plots

box-whisker plots
2.4 Box Plots

C

categorical data
1.2 Data, Sampling, and Variation in Data and Sampling

Categorical variables
1.1 Definitions of Statistics, Probability, and Key Terms

central limit theorem
Introduction,
7.1 The Central Limit Theorem for Sample Means (Averages),
7.3 Using the Central Limit Theorem

central limit theorem for means
7.1 The Central Limit Theorem for Sample Means (Averages)

central limit theorem for sums
7.2 The Central Limit Theorem for Sums (Optional)

chi-square distribution
11.1 Facts About the Chi-Square Distribution

coefficient of determination
12.2 The Regression Equation

complement
3.1 Terminology

confidence level
8.1 A Single Population Mean Using the Normal Distribution,
8.3 A Population Proportion

continuity correction factor
7.3 Using the Central Limit Theorem

continuous random variable
5.3 The Exponential Distribution (Optional)

control group
1.4 Experimental Design and Ethics

critical value
6.2 Using the Normal Distribution

cumulative distribution function
5.1 Continuous Probability Functions

cumulative distribution function (CDF)
5.3 The Exponential Distribution (Optional)

Cumulative relative frequency
1.3 Frequency, Frequency Tables, and Levels of Measurement

D

data
1.1 Definitions of Statistics, Probability, and Key Terms,
1.1 Definitions of Statistics, Probability, and Key Terms

degrees of freedom (

*df*) 10.1 Two Population Means with Unknown Standard Deviations
descriptive statistics
1.1 Definitions of Statistics, Probability, and Key Terms

double-blind experiment
1.4 Experimental Design and Ethics

E

error bound
8.3 A Population Proportion

error bound for a population mean
8.1 A Single Population Mean Using the Normal Distribution

expected value
4.2 Mean or Expected Value and Standard Deviation

expected values
11.2 Goodness-of-Fit Test

Experimental Probability of Event A
3.1 Terminology

exponential distribution
5.3 The Exponential Distribution (Optional),
7.3 Using the Central Limit Theorem

F

*F*distribution 13.2 The F Distribution and the F Ratio

first quartile
2.3 Measures of the Location of the Data

G

geometric distribution
4.4 Geometric Distribution (Optional)

geometric experiment
4.4 Geometric Distribution (Optional)

H

hypergeometric experiment
4 Chapter Review

hypergeometric probability
4.5 Hypergeometric Distribution (Optional)

hypotheses
9.1 Null and Alternative Hypotheses

hypothesis testing.
Introduction

I

independent
3.3 Two Basic Rules of Probability

independent events
3.2 Independent and Mutually Exclusive Events

informed consent
1.4 Experimental Design and Ethics

Institutional Review Boards (IRB)
1.4 Experimental Design and Ethics

interquartile range
2.3 Measures of the Location of the Data

interval scale
1.3 Frequency, Frequency Tables, and Levels of Measurement

L

law of large numbers
7.3 Using the Central Limit Theorem

level of measurement
1.3 Frequency, Frequency Tables, and Levels of Measurement

level of significance of the test
9.4 Rare Events, the Sample, and the Decision and Conclusion

lurking variables
1.4 Experimental Design and Ethics

M

margin of error
Introduction

mathematical models
1.1 Definitions of Statistics, Probability, and Key Terms

mean
1.1 Definitions of Statistics, Probability, and Key Terms,
2.5 Measures of the Center of the Data,
4.2 Mean or Expected Value and Standard Deviation,
Introduction,
7.1 The Central Limit Theorem for Sample Means (Averages),
7.3 Using the Central Limit Theorem

multivariate
Introduction

mutually exclusive
3.2 Independent and Mutually Exclusive Events,
3.3 Two Basic Rules of Probability

N

normal distribution
8.2 A Single Population Mean Using the Student's t-Distribution,
9.3 Distribution Needed for Hypothesis Testing

normally distributed
7.1 The Central Limit Theorem for Sample Means (Averages),
7.2 The Central Limit Theorem for Sums (Optional),
9.3 Distribution Needed for Hypothesis Testing

null hypothesis
9.1 Null and Alternative Hypotheses,
9.4 Rare Events, the Sample, and the Decision and Conclusion

Numerical variables
1.1 Definitions of Statistics, Probability, and Key Terms

O

observational studies
1.4 Experimental Design and Ethics

observed values
11.2 Goodness-of-Fit Test

P

*p*-value 9.4 Rare Events, the Sample, and the Decision and Conclusion, 9.5 Additional Information and Full Hypothesis Test Examples

paired data set
2.2 Histograms, Frequency Polygons, and Time Series Graphs

parameter
Introduction

percentiles
2.3 Measures of the Location of the Data

point estimate
Introduction

pooled proportion
10.3 Comparing Two Independent Population Proportions

population
1.1 Definitions of Statistics, Probability, and Key Terms,
1.2 Data, Sampling, and Variation in Data and Sampling

population variance
11.6 Test of a Single Variance

potential outlier
12.5 Outliers

probability density function
Introduction

probability distribution function
4.1 Probability Distribution Function (PDF) for a Discrete Random Variable

Q

Qualitative data
1.2 Data, Sampling, and Variation in Data and Sampling

quantitative continuous data
1.2 Data, Sampling, and Variation in Data and Sampling

Quantitative data
1.2 Data, Sampling, and Variation in Data and Sampling

quantitative discrete data
1.2 Data, Sampling, and Variation in Data and Sampling

R

random assignment
1.4 Experimental Design and Ethics

Random variable
10.1 Two Population Means with Unknown Standard Deviations,
10.2 Two Population Means with Known Standard Deviations

relative frequency
1.3 Frequency, Frequency Tables, and Levels of Measurement,
2.2 Histograms, Frequency Polygons, and Time Series Graphs

replacement
3.2 Independent and Mutually Exclusive Events

representative sample
1.1 Definitions of Statistics, Probability, and Key Terms

S

sampling distribution
2.5 Measures of the Center of the Data

sampling variability of a statistic
2.7 Measures of the Spread of the Data

simple random sample
9.3 Distribution Needed for Hypothesis Testing

standard deviation
2.7 Measures of the Spread of the Data,
8.2 A Single Population Mean Using the Student's t-Distribution,
9.3 Distribution Needed for Hypothesis Testing,
9.3 Distribution Needed for Hypothesis Testing,
9.4 Rare Events, the Sample, and the Decision and Conclusion,
10.1 Two Population Means with Unknown Standard Deviations

standard deviation of a discrete probability distribution
4.2 Mean or Expected Value and Standard Deviation

standard error
10.1 Two Population Means with Unknown Standard Deviations

standard error of the mean
7.1 The Central Limit Theorem for Sample Means (Averages)

Student's

*t*-distribution 8.2 A Single Population Mean Using the Student's t-Distribution, 9.3 Distribution Needed for Hypothesis Testing, 9.3 Distribution Needed for Hypothesis Testing
sum of squared errors (SSE)
12.2 The Regression Equation

T

test for homogeneity
11.4 Test for Homogeneity

test of a single variance
11.6 Test of a Single Variance

test of independence
11.3 Test of Independence

Theoretical Probability of Event A
3.1 Terminology

tree diagram
3.5 Tree and Venn Diagrams

two-way table
3.4 Contingency Tables

Type I error
9.2 Outcomes and the Type I and Type II Errors,
9.4 Rare Events, the Sample, and the Decision and Conclusion

Type II error
9.2 Outcomes and the Type I and Type II Errors

U

unfair
3.1 Terminology

uniform distribution
7.3 Using the Central Limit Theorem

*Use the following information to answer the next three exercises*3 Homework